A generalized decomposition technique is presented for determining optimal resource usage in segregated targeting problems with single quality index (e.g., concentration, temperature, etc.) through pinch analysis. The latter problems are concerned with determining minimal resource requirements of process networks characterized by the existence of multiple zones, each consisting of a set of demands and using a unique external resource. However, all the zones share a common set of internal sources. The decomposition algorithm allows the problem to be decomposed into a sequence of subproblems, each of which can in turn be solved using any established graphical or algebraic targeting methodology to determine the minimum requirement of respective resource. This article presents a rigorous mathematical proof of the decomposition algorithm, and then demonstrates its potential applications with case studies on carbon-constrained energy sector planning, interplant water integration, and emergy-based multisector fuel allocation.

No abstract

Minimization of the overall resource (e.g., water, hydrogen, material, etc.) requirement and the minimum interplant flow rate to achieve the overall minimum resource requirement across two resource allocation networks (RANs) have been presented in this paper. The resource requirement for a single RAN can be minimized through established mathematical and/or pinch-based methodologies. The overall resource requirement can further be minimized by integrating RANs at the site level. While integrating two RANs at the site level, for the reduction of overall resource requirement, it is also important to minimize the interplant flow rate across them. Mathematically these minimization problems can be modeled as linear programming problems. However, on the basis of the special mathematical features of this problem, an algorithmic procedure as well as a graphical procedure are developed to target the minimum overall resource requirement by integrating two RANs and also to minimize the interplant flow rate, satisfying the previous target. The applicability of the proposed methodology is limited to two RANs with single quality.

A simple modification of the original problem table algorithm (PTA) to target the minimum utility requirements in a heat exchanger network is proposed in this paper. The modified problem table algorithm (MPTA) eliminates the requirement of identification of streams to determine the net heat capacity flow rate at each temperature interval. Targeted utility requirements and the grand composite curve for the heat exchanger network problem are identical for both the original PTA and the proposed MPTA. This simple but fundamental change in the proposed MPTA, enhances its applicability to target the minimum external utility requirements in some special cases of heat-integrated water allocation networks. Pedagogical importance of the proposed MPTA is also discussed.

A mathematical optimization approach for targeting the minimum utility consumption in heat-integrated process water networks is proposed in this paper. The linear programming formulations are developed for heat integration in fixed flow rate water allocation networks, for both single and multiple contaminants, incorporating isothermal mixing. Heat integration in water allocation networks is also addressed through nonisothermal mixing of streams, and this is formulated as a discontinuous nonlinear programming problem. Utility requirements, for isothermal as well as for nonisothermal mixing, are compared over a range of minimum approach temperatures to evaluate the energy performance using illustrative examples. The number of required heat exchangers is less in heat-integrated water allocation problems with nonisothermal mixing. Simultaneous optimization of the overall heat-integrated water allocation network, to minimize the operating cost, is also formulated and solved.